April 1, 2013
Courtesy of Public Library of Science
and World
Science staff

Sci­en­tists say they have rep­li­cat­ed the be­hav­ior of a mov­ing ant col­o­ny us­ing lit­tle ro­bots.

The re­search­ers aimed to learn how ants ori­ent them­selves in the maze­like path­ways along the ground sur­face from their nest to var­i­ous food sources. These trails of­ten fea­ture a tree-like sys­tem of branch­ing points and can ex­tend as far as a quar­ter of a kil­o­me­ter (al­most a sixth of a mile) for some ant spe­cies.

Robot ants pursue a light trail.
(Cour­tesy of S. Gar­nier et al)

The re­search re­vealed ants don’t need great smarts to find efficient
pathways, and it also “points to­ward pos­si­ble im­prove­ments for the de­sign of man-made trans­port­a­t­ion net­works,” wrote the sci­en­tists.
They de­scribed their re­search
in a paper
on­line March 28 in the jour­nal PLoS Com­put­a­t­ional Bi­ol­o­gy.

The work fo­cused on how Ar­gen­tine ants be­have and co­or­di­nate them­selves in sym­met­ri­cal and asym­met­ri­cal path­ways. Re­al ants do this by leav­ing trails of chem­i­cals, called pheromones.

The re­search­ers, at the New Jer­sey In­sti­tute of Tech­nol­o­gy and the Re­search Cen­ter on An­i­mal Cog­ni­tion in Tou­louse, France, re­pro­duced the ac­tiv­ity with a swarm of sug­ar cube-sized ro­bots. The ex­pe­ri­ment was set up so that a vi­deo
pro­jec­tor would light up the ground along the path just fol­lowed by each ro­bot. This pro­cess cre­at­ed lu­mi­nous trails mim­ick­ing “pheromone” trails. Oth­er ro­bots could de­tect the trails us­ing two light sen­sors mim­ick­ing ants’ an­ten­nae.

At the out­set, where branches of the maze had no light trail, the ro­bots adopt­ed an “ex­ploratory be­havior” mod­eled on the reg­u­lar in­sect move­ment pat­tern of mov­ing ran­domly but in the same gen­er­al di­rec­tion. This led the ro­bots to choose the path that de­vi­at­ed least from their tra­jec­to­ry at each branch­ing point of the net­work. If the ro­bots de­tected a light trail, they would turn to fol­low that path.

It turned out they did­n’t need to be pro­grammed to iden­ti­fy and com­pute the ge­om­e­try of the branch
points, the sci­en­tists said. The machines man­aged to nav­i­gate the maze us­ing only the light trail and the pro­grammed di­rec­tional ran­dom walk, which di­rect­ed them to the more di­rect route be­tween their start­ing ar­ea and a tar­get ar­ea on the
edge of the maze.

Ar­gen­tine ants have poor eye­sight and move too quickly to make a cal­cu­lat­ed de­ci­sion about their di­rec­tion, the re­search­ers not­ed. So the fact that the ro­bots man­aged to ori­ent them­selves in the maze the way real ants do sug­gests these in­sects don’t need a com­plex cog­ni­tive pro­cess to nav­i­gate ef­fi­cient­ly, they added.

“This re­search sug­gests that ef­fi­cient navig­a­t­ion and for­ag­ing can be achieved with min­i­mal cog­ni­tive abil­i­ties in ants,” said lead au­thor Si­mon Gar­nier of the New Jer­sey In­sti­tute. “It al­so shows that the ge­om­e­try of trans­port net­works plays a crit­i­cal role in the flow of in­form­a­t­ion and ma­te­ri­al in ant as well as in hu­man so­ci­eties.”

Scientists say they have replicated the behaviour of a moving ant colony using little robots.
The researchers aimed to learn how ants orient themselves in the mazelike pathways along the ground surface from their nest to various food sources. These trails often feature a tree-like system of branch points and can extend as far as a quarter of a kilometer (almost a sixth of a mile) for some ant species.
The research “points toward possible improvements for the design of man-made transport ation networks,” wrote the scientists, describing their research in the journal PLoS Comput ational Biology.
The work focused on how Argentine ants behave and coordinate themselves in symmetrical and asymmetrical pathways. Real ants do this by leaving trails of chemicals, called pheromones.
The researchers, at the New Jersey Institute of Technology and the Research Centre on Animal Cognition in Toulouse, France, reproduced the activ ity with a swarm of sugar cube-sized robots. The experi ment was set up so that a video projector would light up the ground along the path just followed by each robot. This process created luminous trails mimicking “pheromone” trails. Other robots could detect the trails using two light sensors mimicking ants’ antennae.
At the outset, where branches of the maze had no light trail, the robots adopted an “exploratory behaviour” modelled on the regular insect movement pattern of moving random ly but in the same general direction. This led the robots to choose the path that deviated least from their trajectory at each branching point of the network. If the robots detected a light trail, they would turn to follow that path.
It turned out they didn’t need to be programmed to identify and compute the geometry of the branchings, the scientists said. The machines managed to navigate the maze using on ly the light trail and the programmed directional random walk, which directed them to the more direct route between their starting area and a target area on the periphery of the maze.
Individual Argentine ants have poor eyesight and move too quick ly to make a calculated decision about their direction, the researchers noted. So the fact that the robots managed to orient themselves in the maze the way real ants do suggests these insects don’t need a complex cognitive process to navigate efficiently, they added.
“This research suggests that efficient navig ation and foraging can be achieved with minimal cognitive abil ities in ants,” said lead author Simon Garnier of the New Jersey Institute. “It also shows that the geometry of transport networks plays a critical role in the flow of inform ation and material in ant as well as in human societies.”